A computational theory of visual surface interpolation.

Abstract

Computational theories of structure-from-motion and stereo vision only specify the computation of three-dimensional surface information at special points in the image. Yet the visual perception is clearly of complete surfaces. To account for this a computational theory of the interpolation of surfaces from visual information is presented. The problem is constrained by the fact that the surface must agree with the information from stereo or motion correspondence, and not vary radically between these points. Using the image irradiance equation, an explicit form of this surface consistency constraint can be derived. To determine which of two possible surfaces is more consistent with the surface consistency constraint, one must be able to compare the two surfaces. To do this, a functional from the space of possible functions to the real numbers is required. In this way, the surface most consistent with the visual information will be that which minimizes the functional. To ensure that the functional has a unique minimal surface, conditions on the form of the functional are derived. In particular, if the functional is a complete semi-norm that satisfies the parallelogram law, or the space of functions is a semi-Hilbert space and the functional is a semi-inner product, then there is a unique (to within possibly an element of the null space of the functional) surface that is most consistent with the visual information. It can be shown, based on the above conditions plus a condition of rotational symmetry, that there is a vector space of possible functionals that measure surface consistency, this vector space being spanned by the functional of quadratic variation and the functional of square Laplacian. Arguments based on the null spaces of the respective functionals are used to justify the choice of the quadratic variation as the optimal functional. Possible refinements to the theory, concerning the role of discontinuities in depth and the effects of applying the interpolation process to scenes containing more than one object, are discussed.